TrueFidelity for GSI images, 1.25 mm - Pancreatic cancer, BMI 22, CTDIvol
Iodine color map
GE Healthcare is industry first to apply
deep learning-based image reconstruction to dual-energy
spectral CT. It results in generating
high quality GSI images with
reduced image noise¹, improved CNR² and
preferred noise texture⁴.
Deep Learning Image Reconstruction for GSI generates
TrueFidelity GSI images for all GSI image types
TRUEFIDELITY GSI IMAGES
images (40-140 keV)
Material images (iodine, water, calcium, HAP, uric acid, fat)
Virtual Unenhanced images (VUE)
MAR images (GSI MAR)
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Standard deviation in images reconstructed from the
same raw data, at 0.625 mm with DLIR-H and ASiR-V50%.
Demonstrated in testing using images of the CT ACR 464
Phantom (Gammex) and its 25 mm low contrast cylinder
reconstructed from the same raw data with DLIR-L, DILR-M,
and DLIR-H and ASiR-V50%.
Evaluated using the body MITA CT IQ Low Contrast Phantom
(CCT189, the Phantom Laboratory) with the CTP579 oval
body annulus and a model observer with images reconstructed
from the same raw data with DLIR-H and ASiR-V50%.
As demonstrated in a clinical evaluation consisting
of 40 cases and 5 physicians, where each case was reconstructed
with both DLIR for GSI and ASiR-V and evaluated by
3 of the physicians. In 88% of the reads, DLIR for
GSI's noise texture was rated better than ASiR-V's.
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